| 2010 – 2014 || DeepMind initiates as a British AI startup. Before being acquired by {{w|Google}}, it remains relatively unknown.<ref>{{cite web |title=How Google's Amazing AI Start-Up 'DeepMind' Is Making Our World A Smarter Place |url=https://www.forbes.com/sites/bernardmarr/2017/02/02/how-googles-amazing-ai-start-up-deepmind-is-making-our-world-a-smarter-place/#43263b6edfff |website=forbes.com |accessdate=1 June 2019}}</ref>

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| 2010–2014 || DeepMind initiates as a British AI startup. Before being acquired by {{w|Google}}, it remains relatively unknown.<ref>{{cite web |title=How Google's Amazing AI Start-Up 'DeepMind' Is Making Our World A Smarter Place |url=https://www.forbes.com/sites/bernardmarr/2017/02/02/how-googles-amazing-ai-start-up-deepmind-is-making-our-world-a-smarter-place/#43263b6edfff |website=forbes.com |accessdate=1 June 2019}}</ref>

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| 2014 < || Google's DeepMind era. The acquired company starts being known worldwide. Since being acquired by Google, DeepMind's AI would be used to beat humans at board games and create free apps with the British {{w|National Health Service}}. Neither application would make profit for Google so far.<ref name="Google's $500+ million purchase of DeepMind just got very interesting"/>

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| Since 2014 || Google's DeepMind era. The acquired company starts being known worldwide. Since being acquired by Google, DeepMind's AI would be used to beat humans at board games and create free apps with the British {{w|National Health Service}}.<ref name="Google's $500+ million purchase of DeepMind just got very interesting"/>

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| 2016 < || DeepMind becomes renowned after its {{W|AlphaGo}} program beats a human professional Go player for the first time and again when AlphaGo beats {{W|Lee Sedol}}, the world champion, in a five-game match.<ref>{{cite web |title=DeepMind |url=https://paganresearch.io/details/deepmind |website=paganresearch.io |accessdate=5 June 2019}}</ref>

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| Since 2016 || DeepMind becomes renowned after its {{W|AlphaGo}} program beats a human professional Go player for the first time and again when AlphaGo beats {{W|Lee Sedol}}, the world champion, in a five-game match.<ref>{{cite web |title=DeepMind |url=https://paganresearch.io/details/deepmind |website=paganresearch.io |accessdate=5 June 2019}}</ref>

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| Present time || DeepMind is considered today one of the leading {{w|AI}} companies in the world. It has a team of around 700 people, with most of those based out of Google's headquarters in {{w|King's Cross, London}}.<ref name="DeepMind Built An iPhone Space Simulation Game, But Never Released It">{{cite web |title=DeepMind Built An iPhone Space Simulation Game, But Never Released It |url=https://www.forbes.com/sites/samshead/2018/11/02/deepmind-built-an-iphone-space-simulation-game-but-never-released-it/#3d1ec80e662a |website=forbes.com |accessdate=5 June 2019}}</ref>

| Present time || DeepMind is considered today one of the leading {{w|AI}} companies in the world. It has a team of around 700 people, with most of those based out of Google's headquarters in {{w|King's Cross, London}}.<ref name="DeepMind Built An iPhone Space Simulation Game, But Never Released It">{{cite web |title=DeepMind Built An iPhone Space Simulation Game, But Never Released It |url=https://www.forbes.com/sites/samshead/2018/11/02/deepmind-built-an-iphone-space-simulation-game-but-never-released-it/#3d1ec80e662a |website=forbes.com |accessdate=5 June 2019}}</ref>

| 2013 || December || {{w|AI}} development || DeepMind reveals having developed an AI algorithm able to learn how to play iconic early video games like [[w:Breakout (video game)|Breakout]] and {{w|Pong}} simply by watching them being played on a vintage 1977 Atari 2600 games console. Having surmised the rules and rewards from the way the pixels were batted about the screen, the algorithm is then able to beat human opponents at playing the games.<ref name="Google buys AI firm DeepMind to boost image search">{{cite web |title=Google buys AI firm DeepMind to boost image search |url=https://www.newscientist.com/article/dn24946-google-buys-ai-firm-deepmind-to-boost-image-search/ |website=newscientist.com |accessdate=28 May 2019}}</ref>

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| 2013 || December || {{w|AI}} development || DeepMind reveals having developed an AI algorithm able to learn how to play iconic early video games like [[w:Breakout (video game)|Breakout]] and {{w|Pong}} simply by watching them being played on a vintage 1977 Atari 2600 games console. The algorithm deduces the rules and rewards from the way the pixels are batted about the screen, then it is able to beat human opponents at playing the games.<ref name="Google buys AI firm DeepMind to boost image search">{{cite web |title=Google buys AI firm DeepMind to boost image search |url=https://www.newscientist.com/article/dn24946-google-buys-ai-firm-deepmind-to-boost-image-search/ |website=newscientist.com |accessdate=28 May 2019}}</ref>

| 2014 || October 29 || {{w|AI}} development || DeepMind unveils a neural network that can access an external memory like a conventional {{w|Turing machine}}. The project mimics properties of the human brain's short-term working memory. The result is a computer able to mimic some of the brain’s memory skills and even program like a human.<ref>{{cite web |title=Google's Secretive DeepMind Startup Unveils a "Neural Turing Machine" |url=https://www.technologyreview.com/s/532156/googles-secretive-deepmind-startup-unveils-a-neural-turing-machine/ |website=technologyreview.com |accessdate=29 May 2019}}</ref><ref>{{cite web |last1=Hornyak |first1=Tim |title=Google's DeepMind AI project apes human memory and programming skills |url=https://www.pcworld.com/article/2841232/google-ai-project-apes-memory-programs-sort-of-like-a-human.html |website=pcworld.com |accessdate=29 May 2019}}</ref><ref>{{cite web |title=Computer with human-like learning will program itself |url=https://www.newscientist.com/article/mg22429932-200-computer-with-human-like-learning-will-program-itself/ |website=newscientist.com |accessdate=29 May 2019}}</ref><ref>{{cite web |title=Google reveals it is developing a computer so smart it can program ITSELF |url=https://www.dailymail.co.uk/sciencetech/article-2813303/Google-reveals-developing-computer-smart-program-ITSELF.html |website=dailymail.co.uk |accessdate=29 May 2019}}</ref>

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| 2014 || October 29 || {{w|AI}} development || DeepMind unveils a neural network that can access an external memory like a conventional {{w|Turing machine}}. The project mimics properties of the human brain's short-term working memory. The result is a computer able to mimic some of the brain’s memory skills and even program like a human.<ref>{{cite web |title=Google's Secretive DeepMind Startup Unveils a "Neural Turing Machine" |url=https://www.technologyreview.com/s/532156/googles-secretive-deepmind-startup-unveils-a-neural-turing-machine/ |website=technologyreview.com |accessdate=29 May 2019}}</ref><ref>{{cite web |last1=Hornyak |first1=Tim |title=Google's DeepMind AI project apes human memory and programming skills |url=https://www.pcworld.com/article/2841232/google-ai-project-apes-memory-programs-sort-of-like-a-human.html |website=pcworld.com |accessdate=29 May 2019}}</ref><ref>{{cite web |title=Computer with human-like learning will program itself |url=https://www.newscientist.com/article/mg22429932-200-computer-with-human-like-learning-will-program-itself/ |website=newscientist.com |accessdate=29 May 2019}}</ref><ref>{{cite web |title=Google reveals it is developing a computer so smart it can program ITSELF |url=https://www.dailymail.co.uk/sciencetech/article-2813303/Google-reveals-developing-computer-smart-program-ITSELF.html |website=dailymail.co.uk |accessdate=29 May 2019}}</ref>

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| 2014 || November || Notable comment || {{w|Elon Musk}} submits a comment to <code>edge.com</code> about the threat of AI:

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{{Quote|The pace of progress in artificial intelligence (I'm not referring to narrow AI) is incredibly fast. Unless you have direct exposure to groups like Deepmind, you have no idea how fast-it is growing at a pace close to exponential. The risk of something seriously dangerous happening is in the five year timeframe. 10 years at most. This is not a case of crying wolf about something I don't understand.

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I am not alone in thinking we should be worried. The leading AI companies have taken great steps to ensure safety. The recognize the danger, but believe that they can shape and control the digital superintelligences and prevent bad ones from escaping into the Internet. That remains to be seen...}}<ref>{{cite web |title=28 Best Quotes About Artificial Intelligence |url=https://www.bernardmarr.com/default.asp?contentID=1158 |website=bernardmarr.com |accessdate=29 June 2019}}</ref>

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| 2014 || || Recognition || DeepMind receives the "Company of the Year" award from {{w|Cambridge Computer Laboratory}}.<ref>{{cite web|title=Hall of Fame Awards: To celebrate the success of companies founded by Computer Laboratory graduates.|url=https://www.cl.cam.ac.uk/ring/awards.html|publisher=University of Cambridge|accessdate=28 May 2019}}</ref>

| 2014 || || Recognition || DeepMind receives the "Company of the Year" award from {{w|Cambridge Computer Laboratory}}.<ref>{{cite web|title=Hall of Fame Awards: To celebrate the success of companies founded by Computer Laboratory graduates.|url=https://www.cl.cam.ac.uk/ring/awards.html|publisher=University of Cambridge|accessdate=28 May 2019}}</ref>

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| 2015 || June || Notable quote || {{w|Mustafa Suleyman}} describes DeepMind's work during a {{w|machine learning}} conference in {{w|London}}: "Our deep learning tool has now been deployed in many environments, particularly across Google in many of our production systems."<ref name="Google DeepMind: the story behind the world's leading AI startup"/>

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| 2015 || June || Notable comment || {{w|Mustafa Suleyman}} describes DeepMind's work during a {{w|machine learning}} conference in {{w|London}}: {{Quote|"Our deep learning tool has now been deployed in many environments, particularly across Google in many of our production systems."}}<ref name="Google DeepMind: the story behind the world's leading AI startup"/>

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| 2015 || September || Partnership || DeepMind partners with the Royal Free NHS Trust to develop a patient safety app called Streams, aimed at reviewing test results for signs of sickness and sending staff instant alerts if an urgent assessment is required. The app would also help clinicians to quickly check for other serious conditions such as acute kidney injury and display results of blood tests, scans, and x-rays at the touch of a button.<ref name="Google DeepMind: the story behind the world's leading AI startup"/><ref>{{Cite news|url=https://techcrunch.com/2017/08/31/documents-detail-deepminds-plan-to-apply-ai-to-nhs-data-in-2015/|title=Documents detail DeepMind’s plan to apply AI to NHS data in 2015|last=Lomas|first=Natasha|work=TechCrunch|access-date=28 May 2019|language=en}}</ref>

| 2015 || September || Partnership || DeepMind partners with the Royal Free NHS Trust to develop a patient safety application aimed at reviewing test results for signs of sickness and sending staff instant alerts if an urgent assessment is required. The app would also help clinicians to quickly check for other serious conditions such as acute kidney injury and display results of blood tests, scans, and x-rays at the touch of a button.<ref name="Google DeepMind: the story behind the world's leading AI startup"/><ref>{{Cite news|url=https://techcrunch.com/2017/08/31/documents-detail-deepminds-plan-to-apply-ai-to-nhs-data-in-2015/|title=Documents detail DeepMind’s plan to apply AI to NHS data in 2015|last=Lomas|first=Natasha|work=TechCrunch|access-date=28 May 2019|language=en}}</ref>

| 2016 || February || Partnership || DeepMind announces that it is teaming with the {{w|National Health Service}} to build an app called Streams to help hospital staff monitor patients with kidney disease.<ref name="newscientist.com">{{cite web |title=Revealed: Google AI has access to huge haul of NHS patient data |url=https://www.newscientist.com/article/2086454-revealed-google-ai-has-access-to-huge-haul-of-nhs-patient-data/ |website=newscientist.com |accessdate=28 May 2019}}</ref>

| 2016 || February || Partnership || DeepMind announces that it is teaming with the {{w|National Health Service}} to build an app called Streams to help hospital staff monitor patients with kidney disease.<ref name="newscientist.com">{{cite web |title=Revealed: Google AI has access to huge haul of NHS patient data |url=https://www.newscientist.com/article/2086454-revealed-google-ai-has-access-to-huge-haul-of-nhs-patient-data/ |website=newscientist.com |accessdate=28 May 2019}}</ref>

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| 2016 || April || Controversy || ''{{w|New Scientist}}'' obtains a copy of a data-sharing agreement between DeepMind and the {{w|Royal Free London NHS Foundation Trust}}. The latter operates three London hospitals where an estimated 1.6 million patients are treated annually. The agreement shows DeepMind Health had access to admissions, discharge and transfer data, accident and emergency, pathology and radiology, and critical care at these hospitals, including personal details such as whether patients have been diagnosed with [[w:HIV/AIDS|HIV]], suffered from [[w:major depressive disorder|depression]] or have ever undergone an {{w|abortion}} in order to conduct research to seek better outcomes in various health conditions.<ref>{{cite news |url=https://www.newscientist.com/article/2086454-revealed-google-ai-has-access-to-huge-haul-of-nhs-patient-data |title=Revealed: Google AI has access to huge haul of NHS patient data |first=Hal |last=Hodson |work={{w|New Scientist}} |date=29 April 2016 |accessdate= 28 May 2019}}</ref><ref>{{cite news |url=https://www.newscientist.com/article/mg23030722-900-big-data-if-theres-nothing-to-hide-why-be-secretive/ |title=Leader: If Google has nothing to hide about NHS data, why so secretive? |work={{w|New Scientist}} |date=4 May 2016 |accessdate= 28 May 2019}}</ref>

| 2016 || April || Controversy || ''{{w|New Scientist}}'' obtains a copy of a data-sharing agreement between DeepMind and the {{w|Royal Free London NHS Foundation Trust}}. The latter operates three London hospitals where an estimated 1.6 million patients are treated annually. The agreement shows DeepMind Health had access to admissions, discharge and transfer data, accident and emergency, pathology and radiology, and critical care at these hospitals, including personal details such as whether patients have been diagnosed with [[w:HIV/AIDS|HIV]], suffered from [[w:major depressive disorder|depression]] or have ever undergone an {{w|abortion}} in order to conduct research to seek better outcomes in various health conditions.<ref>{{cite news |url=https://www.newscientist.com/article/2086454-revealed-google-ai-has-access-to-huge-haul-of-nhs-patient-data |title=Revealed: Google AI has access to huge haul of NHS patient data |first=Hal |last=Hodson |work={{w|New Scientist}} |date=29 April 2016 |accessdate= 28 May 2019}}</ref><ref>{{cite news |url=https://www.newscientist.com/article/mg23030722-900-big-data-if-theres-nothing-to-hide-why-be-secretive/ |title=Leader: If Google has nothing to hide about NHS data, why so secretive? |work={{w|New Scientist}} |date=4 May 2016 |accessdate= 28 May 2019}}</ref>

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| 2016 || June 3 || {{w|AI}} development || DeepMind develops a ‘big red button’ to stop AIs from causing harm, using a framework in the form of "safely interruptible" artificial intelligence. The system guarantees that a machine will not learn to resist attempts by humans to intervene in its learning processes.<ref>{{cite web |last1=Byrne |first1=Michael |title=Google DeepMind Researchers Develop AI Kill Switch |url=https://www.vice.com/en_us/article/bmv7x5/google-researchers-have-come-up-with-an-ai-kill-switch |website=vice.com |accessdate=30 May 2019}}</ref><ref>{{cite web |last1=Li |first1=Abner |title=Google DeepMind has developed a ‘big red button’ to stop AIs from causing harm |url=https://9to5google.com/2016/06/03/google-deepmind-big-red-button-ai/ |website=9to5google.com |accessdate=30 May 2019}}</ref><ref>{{cite web |last1=Shead |first1=Sam |title=Google has developed a 'big red button' that can be used to interrupt artificial intelligence and stop it from causing harm |url=https://www.businessinsider.com/google-deepmind-develops-a-big-red-button-to-stop-dangerous-ais-causing-harm-2016-6 |website=businessinsider.com |accessdate=30 May 2019}}</ref>

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| 2016 || June 3 || {{w|AI}} development || DeepMind develops a ‘big red button’ to stop AIs from causing harm, using a framework in the form of "safely interruptible" artificial intelligence. It guarantees that a machine will not learn to resist attempts by humans to intervene in its learning processes.<ref>{{cite web |last1=Byrne |first1=Michael |title=Google DeepMind Researchers Develop AI Kill Switch |url=https://www.vice.com/en_us/article/bmv7x5/google-researchers-have-come-up-with-an-ai-kill-switch |website=vice.com |accessdate=30 May 2019}}</ref><ref>{{cite web |last1=Li |first1=Abner |title=Google DeepMind has developed a ‘big red button’ to stop AIs from causing harm |url=https://9to5google.com/2016/06/03/google-deepmind-big-red-button-ai/ |website=9to5google.com |accessdate=30 May 2019}}</ref><ref>{{cite web |last1=Shead |first1=Sam |title=Google has developed a 'big red button' that can be used to interrupt artificial intelligence and stop it from causing harm |url=https://www.businessinsider.com/google-deepmind-develops-a-big-red-button-to-stop-dangerous-ais-causing-harm-2016-6 |website=businessinsider.com |accessdate=30 May 2019}}</ref>. The system is described in a paper by Laurent Orseau from DeepMind and Stuart Armstrong from the {{w|Future of Humanity Institute}}.<ref>{{cite web |title=Safely Interruptible Agents |url=https://intelligence.org/files/Interruptibility.pdf |website=intelligence.org |accessdate=11 June 2019}}</ref>

| 2016 || August 30 || Partnership || DeepMind announces a partnership with {{w|University College London Hospital}} to explore using artificial intelligence to treat patients with head and neck cancers. The goal is to develop tools to automatically identify cancerous cells for {{w|radiology}} machines.<ref>{{cite web |title=Google is teaming up with a London hospital to inject AI into cancer treatment |url=https://qz.com/769974/google-deepmind-cancer-artificial-intelligence-deep-learning-university-college-london-hospital/ |website=qz.com |accessdate=30 May 2019}}</ref><ref>{{cite web |title=Google DeepMind targets NHS head and neck cancer treatment |url=https://www.bbc.com/news/technology-37230806 |website=bbc.com |accessdate=30 May 2019}}</ref><ref>{{cite web |title=Google DeepMind and UCLH collaborate on AI-based radiotherapy treatment |url=https://www.theguardian.com/technology/2016/aug/30/google-deepmind-ucl-ai-radiotherapy-treatment- |website=theguardian.com |accessdate=30 May 2019}}</ref><ref>{{cite web |title=Google DeepMind wants to use machine learning to help treat certain cancers |url=https://www.theverge.com/2016/8/30/12714428/google-deepmind-cancer-treatment-plans-uk-health |website=theverge.com |accessdate=30 May 2019}}</ref>

| 2016 || August 30 || Partnership || DeepMind announces a partnership with {{w|University College London Hospital}} to explore using artificial intelligence to treat patients with head and neck cancers. The goal is to develop tools to automatically identify cancerous cells for {{w|radiology}} machines.<ref>{{cite web |title=Google is teaming up with a London hospital to inject AI into cancer treatment |url=https://qz.com/769974/google-deepmind-cancer-artificial-intelligence-deep-learning-university-college-london-hospital/ |website=qz.com |accessdate=30 May 2019}}</ref><ref>{{cite web |title=Google DeepMind targets NHS head and neck cancer treatment |url=https://www.bbc.com/news/technology-37230806 |website=bbc.com |accessdate=30 May 2019}}</ref><ref>{{cite web |title=Google DeepMind and UCLH collaborate on AI-based radiotherapy treatment |url=https://www.theguardian.com/technology/2016/aug/30/google-deepmind-ucl-ai-radiotherapy-treatment- |website=theguardian.com |accessdate=30 May 2019}}</ref><ref>{{cite web |title=Google DeepMind wants to use machine learning to help treat certain cancers |url=https://www.theverge.com/2016/8/30/12714428/google-deepmind-cancer-treatment-plans-uk-health |website=theverge.com |accessdate=30 May 2019}}</ref>

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| 2016 || September 9 || {{w|AI}} development || DeepMind claims having significantly improved computer-generated speech with its new system called WaveNet, an AI technology making machines sound more like humans. The system generates voices by sampling real human speech and directly modeling audio waveforms based on it, as well as its previously generated audio.<ref>{{cite web |title=Google's DeepMind artificial intelligence has figured out how to talk |url=https://www.businessinsider.com/google-deepmind-wavenet-speech-2016-9 |website=businessinsider.com |accessdate=29 May 2019}}</ref><ref>{{cite web |last1=Gallego |first1=Jelor |title=At Last, Google’s DeepMind AI Can Make Machines Sound Like Humans |url=https://futurism.com/at-last-googles-deepmind-ai-can-make-machines-sound-like-humans |website=futurism.com |accessdate=29 May 2019}}</ref><ref>{{cite web |last1=Robertson |first1=Adi |title=Google’s DeepMind AI fakes some of the most realistic human voices yet |url=https://www.theverge.com/2016/9/9/12860866/google-deepmind-wavenet-ai-text-to-speech-synthesis |website=theverge.com |accessdate=29 May 2019}}</ref><ref>{{cite web |last1=Krumins |first1=Aaron |title=Robots receive a scary-accurate new voice, courtesy of Google’s DeepMind |url=https://www.extremetech.com/extreme/235428-robots-receive-a-scary-new-voice-courtesy-of-googles-deepmind |website=extremetech.com |accessdate=29 May 2019}}</ref>

| 2016 || September 9 || {{w|AI}} development || DeepMind claims having significantly improved computer-generated speech with its new system called WaveNet, an AI technology making machines sound more like humans. The system generates voices by sampling real human speech and directly modeling audio waveforms based on it, as well as its previously generated audio.<ref>{{cite web |title=Google's DeepMind artificial intelligence has figured out how to talk |url=https://www.businessinsider.com/google-deepmind-wavenet-speech-2016-9 |website=businessinsider.com |accessdate=29 May 2019}}</ref><ref>{{cite web |last1=Gallego |first1=Jelor |title=At Last, Google’s DeepMind AI Can Make Machines Sound Like Humans |url=https://futurism.com/at-last-googles-deepmind-ai-can-make-machines-sound-like-humans |website=futurism.com |accessdate=29 May 2019}}</ref><ref>{{cite web |last1=Robertson |first1=Adi |title=Google’s DeepMind AI fakes some of the most realistic human voices yet |url=https://www.theverge.com/2016/9/9/12860866/google-deepmind-wavenet-ai-text-to-speech-synthesis |website=theverge.com |accessdate=29 May 2019}}</ref><ref>{{cite web |last1=Krumins |first1=Aaron |title=Robots receive a scary-accurate new voice, courtesy of Google’s DeepMind |url=https://www.extremetech.com/extreme/235428-robots-receive-a-scary-new-voice-courtesy-of-googles-deepmind |website=extremetech.com |accessdate=29 May 2019}}</ref>

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| 2016 || October 12 || {{w|AI}} development || DeepMind unveils an {{w|AI}} “working memory” able to learn how to solve tasks for itself, such as how best to get from A to B on the London tube network. The AI combines both data processing with self-learning code. The new algorithm is able to retain information in its memory and use its learnings to solve problems in some areas.<ref>{{cite web |title=DeepMind's AI has learned to navigate the Tube using memory |url=https://www.newscientist.com/article/2108934-deepminds-ai-has-learned-to-navigate-the-tube-using-memory/ |website=newscientist.com |accessdate=30 May 2019}}</ref><ref>{{cite web |last1=BURGESS |first1=MATT |title=DeepMind's AI learned to ride the London Underground using human-like reason and memory |url=https://www.wired.co.uk/article/deepmind-ai-tube-london-underground |website=wired.co.uk |accessdate=30 May 2019}}</ref><ref>{{cite web |last1=Hsu |first1=Jeremy |title=Google's Deep Mind Gives AI a Memory Boost That Lets It Navigate London's Underground |url=https://spectrum.ieee.org/tech-talk/computing/software/googles-deep-mind-boosts-memory-to-navigate-london-underground |website=spectrum.ieee.org |accessdate=30 May 2019}}</ref>

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| 2016 || October 12 || {{w|AI}} development || DeepMind unveils an {{w|AI}} “working memory” able to learn how to solve tasks for itself, such as how best to get from A to B on the London tube network. The AI combines both data processing with self-learning code. The new algorithm is able to retain information in its memory and use its learnings to solve problems in some areas.<ref>{{cite web |title=DeepMind's AI has learned to navigate the Tube using memory |url=https://www.newscientist.com/article/2108934-deepminds-ai-has-learned-to-navigate-the-tube-using-memory/ |website=newscientist.com |accessdate=30 May 2019}}</ref><ref>{{cite web |last1=Burgess |first1=Matt |title=DeepMind's AI learned to ride the London Underground using human-like reason and memory |url=https://www.wired.co.uk/article/deepmind-ai-tube-london-underground |website=wired.co.uk |accessdate=30 May 2019}}</ref><ref>{{cite web |last1=Hsu |first1=Jeremy |title=Google's Deep Mind Gives AI a Memory Boost That Lets It Navigate London's Underground |url=https://spectrum.ieee.org/tech-talk/computing/software/googles-deep-mind-boosts-memory-to-navigate-london-underground |website=spectrum.ieee.org |accessdate=30 May 2019}}</ref>

| 2016 || December 5 || Userbase || DeepMind announces open-sourcing DeepMind Lab, its 3D game-like platform for agent-based AI research, so that others can try and make advances in the field of AI. The DeepMind Lab project was used to create enviroments capable of testing AI systems’ ability to achieve goals in a wide range of environments. Tasks such as navigation in mazes, collecting fruit, traversing dangerous passages, laser tag and interaction with bots have been developed to refine the programs. The development of mazes and challenges were designed using video game {{w|Quake III Arena}}’s 17-year-old software, to teach its artificial intelligence programs how to operate in 3D spaces.<ref>{{cite web |last1=McCarthy |first1=John |title=Google DeepMind releases source code to the Quake III levels its using to train AIs |url=https://www.thedrum.com/news/2016/12/05/google-deepmind-releases-source-code-the-quake-iii-levels-its-using-train-ais |website=thedrum.com |accessdate=30 May 2019}}</ref><ref>{{cite web |last1=Condon |first1=Stephanie |title=OpenAI, DeepMind open source AI training platforms |url=https://www.zdnet.com/article/openai-deepmind-open-source-ai-training-platforms/ |website=zdnet.com |accessdate=30 May 2019}}</ref><ref>{{cite web |last1=Shead |first1=Sam |title=DeepMind is opening up its 'flagship' platform to AI researchers outside the company |url=https://www.businessinsider.com/deepmind-opens-up-lab-to-ai-researchers-2016-12 |website=businessinsider.com |accessdate=30 May 2019}}</ref><ref>{{cite web |last1=Kahn |first1=Jeremy |title=Google DeepMind Makes AI Training Platform Publicly Available |url=https://www.bloomberg.com/news/articles/2016-12-05/google-deepmind-makes-ai-training-platform-publicly-available |website=bloomberg.com |accessdate=30 May 2019}}</ref>

| 2016 || December 5 || Userbase || DeepMind announces open-sourcing DeepMind Lab, its 3D game-like platform for agent-based AI research, so that others can try and make advances in the field of AI. The DeepMind Lab project was used to create enviroments capable of testing AI systems’ ability to achieve goals in a wide range of environments. Tasks such as navigation in mazes, collecting fruit, traversing dangerous passages, laser tag and interaction with bots have been developed to refine the programs. The development of mazes and challenges were designed using video game {{w|Quake III Arena}}’s 17-year-old software, to teach its artificial intelligence programs how to operate in 3D spaces.<ref>{{cite web |last1=McCarthy |first1=John |title=Google DeepMind releases source code to the Quake III levels its using to train AIs |url=https://www.thedrum.com/news/2016/12/05/google-deepmind-releases-source-code-the-quake-iii-levels-its-using-train-ais |website=thedrum.com |accessdate=30 May 2019}}</ref><ref>{{cite web |last1=Condon |first1=Stephanie |title=OpenAI, DeepMind open source AI training platforms |url=https://www.zdnet.com/article/openai-deepmind-open-source-ai-training-platforms/ |website=zdnet.com |accessdate=30 May 2019}}</ref><ref>{{cite web |last1=Shead |first1=Sam |title=DeepMind is opening up its 'flagship' platform to AI researchers outside the company |url=https://www.businessinsider.com/deepmind-opens-up-lab-to-ai-researchers-2016-12 |website=businessinsider.com |accessdate=30 May 2019}}</ref><ref>{{cite web |last1=Kahn |first1=Jeremy |title=Google DeepMind Makes AI Training Platform Publicly Available |url=https://www.bloomberg.com/news/articles/2016-12-05/google-deepmind-makes-ai-training-platform-publicly-available |website=bloomberg.com |accessdate=30 May 2019}}</ref>

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| 2017 || January || Collaboration || DeepMind's experts pledge to pass on their knowledge to students enrolled on machine learning master's programs at {{w|University College London}}.<ref>{{cite web |last1=Shead |first1=Sam |title=DeepMind's AI experts have pledged to pass on their knowledge to students at UCL |url=https://www.businessinsider.com/deepmind-ai-experts-are-going-to-teach-at-ucl-2017-1 |website=businessinsider.com |accessdate=1 June 2019}}</ref>

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| 2016 || December || International expansion || DeepMind Applied is anounced as a sub-team to be forming in {{w|Mountain View}}, {{w|California}}. This team is expected to be more closely involved with {{w|Google}}, working with the various product teams to help implement AI-based solutions.<ref>{{cite web |title=New DeepMind Applied Team Being Formed In Mountain View |url=https://www.androidheadlines.com/2016/12/new-deepmind-applied-team-being-formed-in-mountain-view.html |website=androidheadlines.com |accessdate=5 July 2019}}</ref>

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| 2017 || March || {{w|AI}} development || DeepMind announces development of a new way to protect confidential health data from itself, in an attempt to assure hospitals, and the public at large, that patient confidentiality isn’t compromised as DeepMind processes the sensitive medical health records entrusted to it.<ref>{{cite web |last1=Wong |first1=Joon Ian |title=Google’s DeepMind has a plan for protecting private health data—from itself |url=https://qz.com/929833/googles-goog-deepmind-is-using-blockchain-technology-to-handle-nhs-medical-data/ |website=qz.com |accessdate=31 May 2019}}</ref><ref>{{cite web |title=Trust, confidence and Verifiable Data Audit |url=https://deepmind.com/blog/trust-confidence-verifiable-data-audit/ |website=deepmind.com |accessdate=31 May 2019}}</ref>

| 2017 || January || Collaboration || DeepMind's experts pledge to pass on their knowledge to students enrolled on machine learning master's programs at {{w|University College London}}.<ref>{{cite web |last1=Shead |first1=Sam |title=DeepMind's AI experts have pledged to pass on their knowledge to students at UCL |url=https://www.businessinsider.com/deepmind-ai-experts-are-going-to-teach-at-ucl-2017-1 |website=businessinsider.com |accessdate=1 June 2019}}</ref>

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| 2017 || March || {{w|AI}} development || DeepMind announces development of a new way to protect confidential health data from itself, in an attempt to assure hospitals, and the public at large, that patient confidentiality isn’t compromised as DeepMind processes the sensitive medical health records entrusted to it.<ref>{{cite web |last1=Wong |first1=Joon Ian |title=Google’s DeepMind has a plan for protecting private health data—from itself |url=https://qz.com/929833/googles-goog-deepmind-is-using-blockchain-technology-to-handle-nhs-medical-data/ |website=qz.com |accessdate=31 May 2019}}</ref><ref>{{cite web |title=Trust, confidence and Verifiable Data Audit |url=https://deepmind.com/blog/trust-confidence-verifiable-data-audit/ |website=deepmind.com |accessdate=31 May 2019}}</ref>

| 2017 || May || Controversy || ''Sky News'' publishes a leaked letter from the National Data Guardian, [[wikipedia:Fiona Caldicott|Dame Fiona Caldicott]], revealing that in her "considered opinion" the data-sharing agreement between DeepMind and the Royal Free took place on an "inappropriate legal basis".<ref>{{cite news |url=http://news.sky.com/story/google-received-16-million-nhs-patients-data-on-an-inappropriate-legal-basis-10879142/ |title=Google received 1.6 million NHS patients' data on an 'inappropriate legal basis' |first=Alexander J |last=Martin |work={{w|Sky News}} |date=15 May 2017 |accessdate=28 May 2019}}</ref>

| 2017 || May || Controversy || ''Sky News'' publishes a leaked letter from the National Data Guardian, [[wikipedia:Fiona Caldicott|Dame Fiona Caldicott]], revealing that in her "considered opinion" the data-sharing agreement between DeepMind and the Royal Free took place on an "inappropriate legal basis".<ref>{{cite news |url=http://news.sky.com/story/google-received-16-million-nhs-patients-data-on-an-inappropriate-legal-basis-10879142/ |title=Google received 1.6 million NHS patients' data on an 'inappropriate legal basis' |first=Alexander J |last=Martin |work={{w|Sky News}} |date=15 May 2017 |accessdate=28 May 2019}}</ref>

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| 2017 || July || International expansion || DeepMind announces its first international research lab in {{w|Edmonton}}, Canada.<ref>{{cite web |last1=Vincent |first1=James |title=Google’s AI powerhouse DeepMind is opening its first international lab in Canada |url=https://www.theverge.com/2017/7/5/15922574/deepmind-alberta-canda-research-lab |website=theverge.com |accessdate=31 May 2019}}</ref><ref>{{cite web |last1=Fingas |first1=Jon |title=Google's next DeepMind AI research lab opens in Canada |url=https://www.engadget.com/2017/07/05/google-opens-deepmind-lab-in-canada/ |website=engadget.com |accessdate=31 May 2019}}</ref><ref>{{cite web |last1=Kahn |first1=Jeremy |title=DeepMind Goes to Alberta For First International Lab |url=https://www.bloomberg.com/news/articles/2017-07-05/deepmind-goes-to-alberta-for-first-international-lab |website=bloomberg.com |accessdate=31 May 2019}}</ref><ref>{{cite web |last1=SEMENIUK |first1=IVAN |title=AI company that conquered Go game opens office in Edmonton |url=https://www.theglobeandmail.com/news/national/ai-company-that-conquered-go-game-opens-office-in-edmonton/article35551899/ |website=theglobeandmail.com |accessdate=31 May 2019}}</ref>

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| 2017 || June || Partnership || DeepMind’s safety team partners with {{w|OpenAI}} in the development of an algorithm which can infer what humans want by being told which of two proposed behaviors is better. The learning algorithm uses small amounts of human feedback to solve modern {{w|reinforcement learning}} environments.<ref>{{cite web |title=Learning from Human Preferences |url=https://openai.com/blog/deep-reinforcement-learning-from-human-preferences/ |website=openai.com |accessdate=29 June 2019}}</ref>

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| 2017 || July || International expansion || DeepMind announces its first international research lab in {{w|Edmonton}}, Canada.<ref>{{cite web |last1=Vincent |first1=James |title=Google’s AI powerhouse DeepMind is opening its first international lab in Canada |url=https://www.theverge.com/2017/7/5/15922574/deepmind-alberta-canda-research-lab |website=theverge.com |accessdate=31 May 2019}}</ref><ref>{{cite web |last1=Fingas |first1=Jon |title=Google's next DeepMind AI research lab opens in Canada |url=https://www.engadget.com/2017/07/05/google-opens-deepmind-lab-in-canada/ |website=engadget.com |accessdate=31 May 2019}}</ref><ref>{{cite web |last1=Kahn |first1=Jeremy |title=DeepMind Goes to Alberta For First International Lab |url=https://www.bloomberg.com/news/articles/2017-07-05/deepmind-goes-to-alberta-for-first-international-lab |website=bloomberg.com |accessdate=31 May 2019}}</ref><ref>{{cite web |last1=Semeniuk |first1=Ivan |title=AI company that conquered Go game opens office in Edmonton |url=https://www.theglobeandmail.com/news/national/ai-company-that-conquered-go-game-opens-office-in-edmonton/article35551899/ |website=theglobeandmail.com |accessdate=31 May 2019}}</ref>

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| 2017 || July || Controversy || The UK {{w|Information Commissioner's Office}} rules that the Royal Free has breached the Data Protection Act by providing DeepMind with the personal data of around 1.6 million patients.<ref name="Google DeepMind: the story behind the world's leading AI startup"/>

| 2017 || July || Controversy || The UK {{w|Information Commissioner's Office}} rules that the Royal Free has breached the Data Protection Act by providing DeepMind with the personal data of around 1.6 million patients.<ref name="Google DeepMind: the story behind the world's leading AI startup"/>

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| 2017 || Kuly 10 || {{w|AI}} development || DeepMind uses {{w|reinforcement learning}} to master {{w|parkour}}, using a virtual course designed by the researchers which features drops, hurdles, and ledges. All of the navigation is self-taught by the AI using a trial-and-error approach to working out how to move forward and progress across the course as fast as possible.<ref>{{cite web |last1=Vincent |first1=James |title=DeepMind’s AI is teaching itself parkour, and the results are adorable |url=https://www.theverge.com/tldr/2017/7/10/15946542/deepmind-parkour-agent-reinforcement-learning |website=theverge.com |accessdate=31 May 2019}}</ref><ref>{{cite web |last1=Daws |first1=Ryan |title=Google’s DeepMind uses reinforcement learning to master parkour |url=https://www.developer-tech.com/news/2017/jul/10/googles-deepmind-uses-reinforcement-learning-master-parkour/ |website=developer-tech.com |accessdate=31 May 2019}}</ref>

| 2017 || Kuly 10 || {{w|AI}} development || DeepMind uses {{w|reinforcement learning}} to master {{w|parkour}}, using a virtual course designed by the researchers which features drops, hurdles, and ledges. All of the navigation is self-taught by the AI using a trial-and-error approach to working out how to move forward and progress across the course as fast as possible.<ref>{{cite web |last1=Vincent |first1=James |title=DeepMind’s AI is teaching itself parkour, and the results are adorable |url=https://www.theverge.com/tldr/2017/7/10/15946542/deepmind-parkour-agent-reinforcement-learning |website=theverge.com |accessdate=31 May 2019}}</ref><ref>{{cite web |last1=Daws |first1=Ryan |title=Google’s DeepMind uses reinforcement learning to master parkour |url=https://www.developer-tech.com/news/2017/jul/10/googles-deepmind-uses-reinforcement-learning-master-parkour/ |website=developer-tech.com |accessdate=31 May 2019}}</ref>

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| 2017 || July 19 || {{w|AI}} development || DeepMind releases a paper describing new developments for "imagination-based planning" to {{w|AI}} and algorithms that simulate the human ability to construct plans. The AI can reason through decisions and make plans for the future, without being bound by human instructions.<ref>{{cite web |last1=PLUMMER |first1=LIBBY |title=Google's DeepMind creates an AI with 'imagination' |url=https://www.wired.co.uk/article/googles-deepmind-creates-an-ai-with-imagination |website=wired.co.uk |accessdate=29 May 2019}}</ref><ref>{{cite web |last1=Locklear |first1=Mallory |title=DeepMind researchers create AI with an ‘imagination’ |url=https://www.engadget.com/2017/07/25/deepmind-create-ai-imagination/ |website=engadget.com |accessdate=29 May 2019}}</ref><ref>{{cite web |last1=NIELD |first1=DAVID |title=Google Has Started Adding Imagination to Its DeepMind AI |url=https://www.sciencealert.com/google-has-started-adding-imagination-to-its-deepmind-ai |website=sciencealert.com |accessdate=29 May 2019}}</ref><ref>{{cite web |last1=PRIGG |first1=MARK |title=Google's DeepMind researchers create AI with an ‘imagination’ |url=https://www.dailymail.co.uk/sciencetech/article-4730392/Google-s-DeepMind-create-AI-imagination.html |website=dailymail.co.uk |accessdate=29 May 2019}}</ref>

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| 2017 || July 19 || {{w|AI}} development || DeepMind releases a paper describing new developments for "imagination-based planning" to {{w|AI}} and algorithms that simulate the human ability to construct plans. The AI can reason through decisions and make plans for the future, without being bound by human instructions.<ref>{{cite web |last1=Plummer |first1=Libby |title=Google's DeepMind creates an AI with 'imagination' |url=https://www.wired.co.uk/article/googles-deepmind-creates-an-ai-with-imagination |website=wired.co.uk |accessdate=29 May 2019}}</ref><ref>{{cite web |last1=Locklear |first1=Mallory |title=DeepMind researchers create AI with an ‘imagination’ |url=https://www.engadget.com/2017/07/25/deepmind-create-ai-imagination/ |website=engadget.com |accessdate=29 May 2019}}</ref><ref>{{cite web |last1=Nield |first1=David |title=Google Has Started Adding Imagination to Its DeepMind AI |url=https://www.sciencealert.com/google-has-started-adding-imagination-to-its-deepmind-ai |website=sciencealert.com |accessdate=29 May 2019}}</ref><ref>{{cite web |last1=Prigg |first1=Mark |title=Google's DeepMind researchers create AI with an ‘imagination’ |url=https://www.dailymail.co.uk/sciencetech/article-4730392/Google-s-DeepMind-create-AI-imagination.html |website=dailymail.co.uk |accessdate=29 May 2019}}</ref>

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| 2017 || October 4 || Team || DeepMind launches DeepMind Ethics & Society (DMES), a new research group recruiting advisers from academia and charity sector with the purpose to ‘help technologists put ethics into practice’ and help coping with artificial intelligence to consider the “real-world impacts” of replicating human intelligence. The group consists of six independent research fellows, eight full-time researchers, and nine partnerships with other research institutions. It would explore topics such as algorithmic bias, accountability, and autonomous killing machines.<ref>{{cite web |last1=Gershgorn |first1=Dave |title=DeepMind now has two ethics groups, but one of them is still secret |url=https://qz.com/1094283/alphabets-goog-deepmind-now-has-two-ethics-groups-but-one-of-them-is-still-secret/ |website=qz.com |accessdate=31 May 2019}}</ref><ref>{{cite web |last1=Hern |first1=Alex |title=DeepMind announces ethics group to focus on problems of AI |url=https://www.theguardian.com/technology/2017/oct/04/google-deepmind-ai-artificial-intelligence-ethics-group-problems |website=theguardian.com |accessdate=31 May 2019}}</ref><ref>{{cite web |last1=SAWERS |first1=PAUL |title=Alphabet’s DeepMind sets up ‘ethics and society’ unit to research real-world impact of AI |url=https://venturebeat.com/2017/10/04/alphabets-deepmind-sets-up-ethics-and-society-unit-to-research-real-world-impact-of-ai/ |website=venturebeat.com |accessdate=31 May 2019}}</ref>

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| 2017 || October 4 || Team || DeepMind launches DeepMind Ethics & Society (DMES), a new research group recruiting advisers from academia and charity sector with the purpose to ‘help technologists put ethics into practice’ and help coping with artificial intelligence to consider the “real-world impacts” of replicating human intelligence. The group consists of six independent research fellows, eight full-time researchers, and nine partnerships with other research institutions. It would explore topics such as algorithmic bias, accountability, and autonomous killing machines.<ref>{{cite web |last1=Gershgorn |first1=Dave |title=DeepMind now has two ethics groups, but one of them is still secret |url=https://qz.com/1094283/alphabets-goog-deepmind-now-has-two-ethics-groups-but-one-of-them-is-still-secret/ |website=qz.com |accessdate=31 May 2019}}</ref><ref>{{cite web |last1=Hern |first1=Alex |title=DeepMind announces ethics group to focus on problems of AI |url=https://www.theguardian.com/technology/2017/oct/04/google-deepmind-ai-artificial-intelligence-ethics-group-problems |website=theguardian.com |accessdate=31 May 2019}}</ref><ref>{{cite web |last1=Sawers |first1=Paul |title=Alphabet’s DeepMind sets up ‘ethics and society’ unit to research real-world impact of AI |url=https://venturebeat.com/2017/10/04/alphabets-deepmind-sets-up-ethics-and-society-unit-to-research-real-world-impact-of-ai/ |website=venturebeat.com |accessdate=31 May 2019}}</ref>

| 2017 || October 18 || {{w|AI}} development || DeepMind announces AlphaGo Zero, a software capable of mastering the Chinese game of {{w|Go}} without help from human players. The new version is an improvement on the original AlphaGo, which had to be trained over time using large quantities of human knowledge and supervision.<ref>{{cite web |title=AI versus AI: Self-Taught AlphaGo Zero Vanquishes Its Predecessor |url=https://www.scientificamerican.com/article/ai-versus-ai-self-taught-alphago-zero-vanquishes-its-predecessor/?redirect=1 |website=scientificamerican.com |accessdate=11 June 2019}}</ref><ref name="Google DeepMind: AI becomes more alien">{{cite web |last1=Cellan-Jones |first1=Rory |title=Google DeepMind: AI becomes more alien |url=https://www.bbc.com/news/technology-41668701 |website=bbc.com |accessdate=30 May 2019}}</ref><ref>{{cite web |last1=Burgess |first1=Matt |title=DeepMind's latest AI breakthrough is its most significant yet |url=https://www.wired.co.uk/article/deepmind-alphago-zero-nature-reinforcement-learning |website=wired.co.uk |accessdate=30 May 2019}}</ref><ref>{{cite web |last1=Cuthbertson |first1=Anthony |title=Deepmind AlphaGo: AI Teaches Itself 'Thousands of Years of Human Knowledge' Without Help |url=https://www.newsweek.com/deepmind-alphago-ai-teaches-human-help-687620 |website=newsweek.com |accessdate=30 May 2019}}</ref><ref>{{cite web |last1=Shead |first1=Sam |title=DeepMind's human-bashing AlphaGo AI is now even stronger |url=https://www.businessinsider.com/deepminds-alphago-ai-gets-alphago-zero-upgrade-2017-10 |website=businessinsider.com |accessdate=30 May 2019}}</ref>

| 2017 || November || Partnership || DeepMind announces a research partnership with the {{w|Cancer Research UK}} Center at {{w|Imperial College London}} with the goal of improving {{w|breast cancer}} detection by applying {{w|machine learning}} to {{w|mammography}}.<ref>{{cite web|url=https://siliconangle.com/blog/2017/11/24/google-deepmind-announces-new-research-partnership-fight-breast-cancer-ai/|title=Google DeepMind announces new research partnership to fight breast cancer with AI|date=24 November 2017|website=Silicon Angle}}</ref>

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| 2017 || October || International expansion || DeepMind opens new research office in {{w|Montreal}}, led by {{w|McGill University}} professor {{w|Doina Precup}}.<ref>{{cite web |title=DeepMind opens new AI research office in Montreal |url=https://www.linkedin.com/pulse/deepmind-opens-new-research-office-montreal-andres-restrepo/ |website=linkedin.com |accessdate=5 July 2019}}</ref>

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| 2017 || November || Partnership || DeepMind announces a research partnership with the {{w|Cancer Research UK}} Center at {{w|Imperial College London}} with the goal of improving {{w|breast cancer}} detection by applying {{w|machine learning}} to {{w|mammography}}.<ref>{{cite web|url=https://siliconangle.com/blog/2017/11/24/google-deepmind-announces-new-research-partnership-fight-breast-cancer-ai/|title=Google DeepMind announces new research partnership to fight breast cancer with AI|date=24 November 2017|website=Silicon Angle}}</ref>

| 2018 || February || Partnership || DeepMind announces that it is teaming with the [[w:United States Department of Veterans Affairs|U.S. Department of Veterans Affairs]] in an attempt to use machine learning to predict the onset of acute kidney injury in patients, and also more broadly the general deterioration of patients during a hospital stay so that doctors and nurses can more quickly treat patients in need.<ref>{{cite web|url=https://venturebeat.com/2018/02/22/googles-deepmind-wants-ai-to-spot-kidney-injuries/|title=Google's DeepMind wants AI to spot kidney injuries|date=22 February 2018|website=Venture Beat}}</ref>

| 2018 || February || Partnership || DeepMind announces that it is teaming with the [[w:United States Department of Veterans Affairs|U.S. Department of Veterans Affairs]] in an attempt to use machine learning to predict the onset of acute kidney injury in patients, and also more broadly the general deterioration of patients during a hospital stay so that doctors and nurses can more quickly treat patients in need.<ref>{{cite web|url=https://venturebeat.com/2018/02/22/googles-deepmind-wants-ai-to-spot-kidney-injuries/|title=Google's DeepMind wants AI to spot kidney injuries|date=22 February 2018|website=Venture Beat}}</ref>

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| 2018 || February || {{w|AI}} development || DeepMind develops an artificial intelligence able to pass an important psychological assessment that most children only develop the skills to pass at around age 4.<ref>{{cite web |last1=Revell |first1=Timothy |title=DeepMind AI is learning to understand the ‘thoughts’ of others |url=https://www.newscientist.com/article/mg23731673-400-deepmind-ai-is-learning-to-understand-the-thoughts-of-others/ |website=newscientist.com |accessdate=3 June 2019}}</ref><ref>{{cite web |title=Will A.I. Ever Be Smarter Than a Four-Year-Old? |url=https://www.smithsonianmag.com/innovation/will-ai-ever-be-smarter-than-four-year-old-180971259/ |website=smithsonianmag.com |accessdate=3 June 2019}}</ref>

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| 2018 || February || {{w|AI}} development || DeepMind develops an artificial intelligence capable of an ability that most children only develop at around age 4, which is to infer what someone else is thinking. This new technology is thought to have useful application in the future, from warfare to elderly care.<ref>{{cite web |last1=Revell |first1=Timothy |title=DeepMind AI is learning to understand the ‘thoughts’ of others |url=https://www.newscientist.com/article/mg23731673-400-deepmind-ai-is-learning-to-understand-the-thoughts-of-others/ |website=newscientist.com |accessdate=3 June 2019}}</ref><ref>{{cite web |title=Will A.I. Ever Be Smarter Than a Four-Year-Old? |url=https://www.smithsonianmag.com/innovation/will-ai-ever-be-smarter-than-four-year-old-180971259/ |website=smithsonianmag.com |accessdate=3 June 2019}}</ref><ref>{{cite web |title=‘Deep Mind’ AI As Advanced as a 4yr old! |url=https://www.trebuchet-magazine.com/deep-mind-ai-advanced-4yr-old/ |website=trebuchet-magazine.com |accessdate=11 June 2019}}</ref>

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| 2018 || March || International expansion || DeepMind announces a new research lab in {{w|Paris}}, led by Remi Munos.<ref>{{cite web |title=A return to Paris |url=https://deepmind.com/blog/a-return-to-paris/ |website=deepmind.com |accessdate=5 July 2019}}</ref>

| 2018 || June 14 || {{w|AI}} development || DeepMind develops a neural network that teaches itself to ‘imagine’ a scene from different viewpoints, based on just a single image. The new type of computer vision algorithm can generate 3D models of a scene from 2D snapshots, unraveling details from the static images and solving spatial relationships, including the camera’s position. Dubbed a Generative Query Network (GQN), the system gets rid of labels and focuses on what's known as {{w|unsupervised learning}}.<ref>{{cite web |last1=Whyte |first1=Chelsea |title=DeepMind’s AI can ‘imagine’ a world based on a single picture |url=https://www.newscientist.com/article/2171675-deepminds-ai-can-imagine-a-world-based-on-a-single-picture/ |website=newscientist.com |accessdate=1 June 2019}}</ref><ref>{{cite web |last1=Bogle |first1=Ariel |title=Who needs humans? Google's DeepMind algorithm can teach itself to see |url=https://www.abc.net.au/news/science/2018-06-15/googles-deepmind-algorithm-can-teach-itself-to-see/9861590 |website=abc.net |accessdate=1 June 2019}}</ref><ref>{{cite web |last1=Wiggers |first1=Kyle |title=Google’s DeepMind develops AI that can render 3D objects from 2D pictures |url=https://venturebeat.com/2018/06/14/googles-deepmind-develops-ai-that-can-render-3d-objects-from-2d-pictures/ |website=venturebeat.com |accessdate=1 June 2019}}</ref><ref>{{cite web |title=Neural scene representation and rendering |url=https://science.sciencemag.org/content/360/6394/1204 |website=science.sciencemag.org |accessdate=1 June 2019}}</ref>

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| 2018 || June 14 || {{w|AI}} development || DeepMind develops a neural network that teaches itself to ‘imagine’ a scene from different viewpoints, based on just a single image. The new type of computer vision algorithm can generate 3D models of a scene from 2D snapshots. It can tease out details from the static images to guess at spatial relationships, including the camera’s position. Dubbed a Generative Query Network (GQN), the system gets rid of labels and focuses on what's known as {{w|unsupervised learning}}.<ref>{{cite web |last1=Whyte |first1=Chelsea |title=DeepMind’s AI can ‘imagine’ a world based on a single picture |url=https://www.newscientist.com/article/2171675-deepminds-ai-can-imagine-a-world-based-on-a-single-picture/ |website=newscientist.com |accessdate=1 June 2019}}</ref><ref>{{cite web |last1=Bogle |first1=Ariel |title=Who needs humans? Google's DeepMind algorithm can teach itself to see |url=https://www.abc.net.au/news/science/2018-06-15/googles-deepmind-algorithm-can-teach-itself-to-see/9861590 |website=abc.net |accessdate=1 June 2019}}</ref><ref>{{cite web |last1=WIGGERS |first1=KYLE |title=Google’s DeepMind develops AI that can render 3D objects from 2D pictures |url=https://venturebeat.com/2018/06/14/googles-deepmind-develops-ai-that-can-render-3d-objects-from-2d-pictures/ |website=venturebeat.com |accessdate=1 June 2019}}</ref><ref>{{cite web |title=Neural scene representation and rendering |url=https://science.sciencemag.org/content/360/6394/1204 |website=science.sciencemag.org |accessdate=1 June 2019}}</ref>

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| 2018 || June 15 || Controversy || The DeepMind Health Independent Reviewers’ 2018 report warns about the potential for DeepMind Health to be able to “exert excessive monopoly power” as a result of the data access and streaming infrastructure that’s bundled with provision of the Streams app, which would position DeepMind as the access-controlling intermediary between the structured health data and any other third parties.<ref>{{cite web |last1=Lomas |first1=Natasha |title=UK report warns DeepMind Health could gain ‘excessive monopoly power’ |url=https://techcrunch.com/2018/06/15/uk-report-warns-deepmind-health-could-gain-excessive-monopoly-power/ |website=techcrunch.com |accessdate=3 June 2019}}</ref><ref>{{cite web |last1=Lomas |first1=Natasha |title=Building health AIs should be UK ambition, says strategy review |url=https://techcrunch.com/2017/08/31/building-health-ais-should-be-uk-ambition-says-strategy-review/ |website=techcrunch.com |accessdate=3 June 2019}}</ref>

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| 2018 || June 15 || Controversy || The DeepMind Health Independent Reviewers’ 2018 report warns on the potential for DeepMind Health to be able to “exert excessive monopoly power” as a result of the data access and streaming infrastructure that’s bundled with provision of the Streams app, which would position DeepMind as the access-controlling intermediary between the structured health data and any other third parties.<ref>{{cite web |last1=Lomas |first1=Natasha |title=UK report warns DeepMind Health could gain ‘excessive monopoly power’ |url=https://techcrunch.com/2018/06/15/uk-report-warns-deepmind-health-could-gain-excessive-monopoly-power/ |website=techcrunch.com |accessdate=3 June 2019}}</ref><ref>{{cite web |last1=Lomas |first1=Natasha |title=Building health AIs should be UK ambition, says strategy review |url=https://techcrunch.com/2017/08/31/building-health-ais-should-be-uk-ambition-says-strategy-review/ |website=techcrunch.com |accessdate=3 June 2019}}</ref>

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| 2018 || June 26 || || {{w|Demis Hassabis}} is enlisted by the British government's {{w|Department for Digital, Culture, Media and Sport}} (DCMS), as an adviser to the Government’s new {{w|Office for Artificial Intelligence}}.<ref>{{cite web |title=DeepMind co-founder among experts to advise Government on using AI |url=https://www.eveningexpress.co.uk/news/deepmind-co-founder-among-experts-to-advise-government-on-using-ai/ |website=eveningexpress.co.uk |accessdate=3 June 2019}}</ref><ref>{{cite web |title=UK enlists DeepMind's Demis Hassabis to advise its new Government Office for AI |url=https://www.zdnet.com/article/uk-enlists-deepminds-demis-hassabis-to-advise-its-new-government-office-for-ai/ |website=zdnet.com |accessdate=3 June 2019}}</ref>

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| 2018 || June 26 || || Dr {{w|Demis Hassabis}} is enlisted by the British government's {{w|Department for Digital, Culture, Media and Sport}} (DCMS), as an adviser to the Government’s new {{w|Office for Artificial Intelligence}}.<ref>{{cite web |title=DeepMind co-founder among experts to advise Government on using AI |url=https://www.eveningexpress.co.uk/news/deepmind-co-founder-among-experts-to-advise-government-on-using-ai/ |website=eveningexpress.co.uk |accessdate=3 June 2019}}</ref><ref>{{cite web |title=UK enlists DeepMind's Demis Hassabis to advise its new Government Office for AI |url=https://www.zdnet.com/article/uk-enlists-deepminds-demis-hassabis-to-advise-its-new-government-office-for-ai/ |website=zdnet.com |accessdate=3 June 2019}}</ref>

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| 2018 || November 19 || Partnership || DeepMind partners with {{w|OpenAI}} in a new paper that proposes a new method to train {{w|reinforcement learning}} agents in ways that enables them to surpass human performance. The paper, titled ''Reward learning from human preferences and demonstrations in Atari'', introduces a training model that combines human feedback and reward optimization to maximize the knowledge of RL agents.<ref>{{cite web |last1=Rodriguez |first1=Jesus |title=What’s New in Deep Learning Research: OpenAI and DeepMind Join Forces to Achieve Superhuman Performance in Reinforcement Learning |url=https://towardsdatascience.com/whats-new-in-deep-learning-research-openai-and-deepmind-join-forces-to-achieve-superhuman-48e7d1accf85 |website=towardsdatascience.com |accessdate=29 June 2019}}</ref>

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| 2018 || July || {{w|AI}} development || Researchers from DeepMind train one of its systems to play the famous computer game ''{{w|Quake III Arena}}''.<ref>[https://www.engadget.com/2018/07/03/deepmind-ai-quake-iii-arena-human/ "DeepMind AI’s new trick is playing ‘Quake III Arena’ like a human"]. ''Engadget''. 3 July 2018.</ref>

| 2018 || July || {{w|AI}} development || Researchers from DeepMind train one of its systems to play the famous computer game ''{{w|Quake III Arena}}''.<ref>[https://www.engadget.com/2018/07/03/deepmind-ai-quake-iii-arena-human/ "DeepMind AI’s new trick is playing ‘Quake III Arena’ like a human"]. ''Engadget''. 3 July 2018.</ref>

| 2018 || October 4 || {{w|AI}} development || DeepMind furthers cancer research and announces having been given access to {{w|mammogram}}s from roughly 30,000 women that were taken at {{w|Jikei University Hospital}} in {{w|Tokyo}}, {{w|Japan}} between 2007 and 2018. The data would be used to refine DeepMind's AI breast cancer detection algorithms.<ref>{{cite web |last1=Wiggers |first1=Kyle |title=DeepMind expands AI cancer research program to Japan |url=https://venturebeat.com/2018/10/04/deepmind-expands-ai-cancer-research-program-to-japan/ |website=venturebeat.com |accessdate=3 June 2019}}</ref><ref>{{cite web |last1=Shead |first1=Sam |title=Google DeepMind Given Access To Mammograms Of 30,000 Women By Japanese Hospital |url=https://www.forbes.com/sites/samshead/2018/10/04/google-deepmind-given-access-to-mammograms-of-30000-women-by-japanese-hospital/#280652659baa |website=forbes.com |accessdate=3 June 2019}}</ref>

| 2018 || October 4 || {{w|AI}} development || DeepMind furthers cancer research and announces having been given access to {{w|mammogram}}s from roughly 30,000 women that were taken at {{w|Jikei University Hospital}} in {{w|Tokyo}}, {{w|Japan}} between 2007 and 2018. The data would be used to refine DeepMind's AI breast cancer detection algorithms.<ref>{{cite web |last1=WIGGERS |first1=KYLE |title=DeepMind expands AI cancer research program to Japan |url=https://venturebeat.com/2018/10/04/deepmind-expands-ai-cancer-research-program-to-japan/ |website=venturebeat.com |accessdate=3 June 2019}}</ref><ref>{{cite web |last1=Shead |first1=Sam |title=Google DeepMind Given Access To Mammograms Of 30,000 Women By Japanese Hospital |url=https://www.forbes.com/sites/samshead/2018/10/04/google-deepmind-given-access-to-mammograms-of-30000-women-by-japanese-hospital/#280652659baa |website=forbes.com |accessdate=3 June 2019}}</ref>

| 2018 || November 13 || Team || As part of a reorganization of its health care efforts, DeepMind announces that its health division and the Streams app would be absorbed into {{w|Google Health}}.<ref>{{cite news |last=Vincent |first=James |url=https://www.theverge.com/2018/11/13/18091774/google-deepmind-health-absorbing-streams-team-ai-assistant-nurse-doctor|title=Google is absorbing DeepMind's health care unit to create an 'AI assistant for nurses and doctors' |work=The Verge |date=13 November 2018 |accessdate=28 May 2019}}</ref><ref>{{cite web |last1=Vincent |first1=James |title=Google is absorbing DeepMind’s health care unit to create an ‘AI assistant for nurses and doctors’ |url=https://www.theverge.com/2018/11/13/18091774/google-deepmind-health-absorbing-streams-team-ai-assistant-nurse-doctor |website=theverge.com |accessdate=30 May 2019}}</ref>

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| 2018 || December || Notable comment || {{w|Demis Hassabis}} announces: {{Quote|"I'd be much more pessimistic about the way the world is going to go if I didn't know there was something as game-changing as AI on the way."}}<ref name="Google DeepMind: the story behind the world's leading AI startup"/>

| 2018 || December || Notable quote || {{w|Demis Hassabis}} announces: {{quote|"I'd be much more pessimistic about the way the world is going to go if I didn't know there was something as game-changing as AI on the way."<ref name="Google DeepMind: the story behind the world's leading AI startup"/>}}

| 2019 || March || Team || As of date, DeepMind has about 700 employees.<ref>{{cite book |last1=Webb |first1=Amy |title=The Big Nine: How the Tech Titans and Their Thinking Machines Could Warp Humanity |url=https://books.google.com.ar/books?id=-9RtDwAAQBAJ&pg=PT55&lpg=PT55&dq=deepmind+%22500..1500%22+employees&source=bl&ots=fxEkpTp_o-&sig=ACfU3U2g7oK7c2Kt5mQv7y6Pb-KJkJ_wgA&hl=en&sa=X&ved=2ahUKEwiw-6-Mu57jAhU_GbkGHQwsD28Q6AEwAHoECAkQAQ#v=onepage&q=deepmind%20%22500..1500%22%20employees&f=false}}</ref>

| 2019 || April || {{w|AI}} development || DeepMind researchers develop an {{w|AI}} tasked with teaching itself to solve arithmetic, algebra and probability problems, among others. However, the neural network performs poorly when tested on a maths exam taken by 16-year-olds in the United Kingdom, getting just 14 out of 40 questions correct, or the equivalent of an E grade.<ref>{{cite web |last1=Vaughan |first1=Adam |title=DeepMind created a maths AI that can add up to 6 but gets 7 wrong |url=https://www.newscientist.com/article/2198761-deepmind-created-a-maths-ai-that-can-add-up-to-6-but-gets-7-wrong/ |website=newscientist.com |accessdate=3 June 2019}}</ref><ref>{{cite web |last1=Srivastava |first1=Smriti |title=DeepMind Examined AI Neural Net Over High School Maths, but Lacked Success |url=https://www.analyticsinsight.net/deepmind-examined-ai-neural-net-over-high-school-maths-but-lacked-success/ |website=analyticsinsight.net |accessdate=3 June 2019}}</ref>

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| 2019 || April || {{w|AI}} development || DeepMind researchers develop an {{w|AI}} tasked with teaching itself to solve arithmetic, algebra and probability problems, among others. However, the neural network performs poorly when tested on a maths exam taken by 16-year-olds in the United Kingdom, getting just 14 out of 40 questions correct, or the equivalent of an E grade.<ref>{{cite web |last1=Vaughan |first1=Adam |title=DeepMind created a maths AI that can add up to 6 but gets 7 wrong |url=https://www.newscientist.com/article/2198761-deepmind-created-a-maths-ai-that-can-add-up-to-6-but-gets-7-wrong/ |website=newscientist.com |accessdate=3 June 2019}}</ref><ref>{{cite web |last1=Srivastava |first1=Smriti |title=DEEPMIND EXAMINED AI NEURAL NET OVER HIGH SCHOOL MATHS, BUT LACKED SUCCESS |url=https://www.analyticsinsight.net/deepmind-examined-ai-neural-net-over-high-school-maths-but-lacked-success/ |website=analyticsinsight.net |accessdate=3 June 2019}}</ref>

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| 2019 || June || {{w|AI}} development || DeepMind medical director Dominic King says {{w|AI}} could soon be used in predictive medicine, achieving this by looking at a medical record and electronic health record data to make predictions.<ref>{{cite web |title=DeepMind health lead says AI could soon be used in predictive medicine |url=https://www.digitalhealth.net/2019/06/deepmind-health-lead-says-ai-could-soon-be-used-in-predictive-medicine/ |website=digitalhealth.net |accessdate=29 June 2019}}</ref>

Contents

Big picture

Time period

Development summary

2010–2014

DeepMind initiates as a British AI startup. Before being acquired by Google, it remains relatively unknown.[1]

Since 2014

Google's DeepMind era. The acquired company starts being known worldwide. Since being acquired by Google, DeepMind's AI would be used to beat humans at board games and create free apps with the British National Health Service.[2]

Since 2016

DeepMind becomes renowned after its AlphaGo program beats a human professional Go player for the first time and again when AlphaGo beats Lee Sedol, the world champion, in a five-game match.[3]

Present time

DeepMind is considered today one of the leading AI companies in the world. It has a team of around 700 people, with most of those based out of Google's headquarters in King's Cross, London.[4]

DeepMind reveals having developed an AI algorithm able to learn how to play iconic early video games like Breakout and Pong simply by watching them being played on a vintage 1977 Atari 2600 games console. The algorithm deduces the rules and rewards from the way the pixels are batted about the screen, then it is able to beat human opponents at playing the games.[11]

DeepMind unveils a neural network that can access an external memory like a conventional Turing machine. The project mimics properties of the human brain's short-term working memory. The result is a computer able to mimic some of the brain’s memory skills and even program like a human.[15][16][17][18]

The pace of progress in artificial intelligence (I'm not referring to narrow AI) is incredibly fast. Unless you have direct exposure to groups like Deepmind, you have no idea how fast-it is growing at a pace close to exponential. The risk of something seriously dangerous happening is in the five year timeframe. 10 years at most. This is not a case of crying wolf about something I don't understand.

I am not alone in thinking we should be worried. The leading AI companies have taken great steps to ensure safety. The recognize the danger, but believe that they can shape and control the digital superintelligences and prevent bad ones from escaping into the Internet. That remains to be seen...

DeepMind partners with the Royal Free NHS Trust to develop a patient safety application aimed at reviewing test results for signs of sickness and sending staff instant alerts if an urgent assessment is required. The app would also help clinicians to quickly check for other serious conditions such as acute kidney injury and display results of blood tests, scans, and x-rays at the touch of a button.[6][22]

DeepMind develops an artificial intelligence capable of learning how to successfully play 49 classic Atari games by itself, with minimal input. The researchers claim software that learns to play video games could graduate to the real world before long.[25][26][27][28]

2016

February

Partnership

DeepMind announces that it is teaming with the National Health Service to build an app called Streams to help hospital staff monitor patients with kidney disease.[29]

2016

February 24

Team

DeepMind launches a new division called DeepMind Health, an initiative aimed at creating apps for medical professionals that can help identify patients at risk of complications.[30][31][32][33]

2016

April

Controversy

New Scientist obtains a copy of a data-sharing agreement between DeepMind and the Royal Free London NHS Foundation Trust. The latter operates three London hospitals where an estimated 1.6 million patients are treated annually. The agreement shows DeepMind Health had access to admissions, discharge and transfer data, accident and emergency, pathology and radiology, and critical care at these hospitals, including personal details such as whether patients have been diagnosed with HIV, suffered from depression or have ever undergone an abortion in order to conduct research to seek better outcomes in various health conditions.[34][35]

DeepMind develops a ‘big red button’ to stop AIs from causing harm, using a framework in the form of "safely interruptible" artificial intelligence. It guarantees that a machine will not learn to resist attempts by humans to intervene in its learning processes.[36][37][38]. The system is described in a paper by Laurent Orseau from DeepMind and Stuart Armstrong from the Future of Humanity Institute.[39]

DeepMind claims having significantly improved computer-generated speech with its new system called WaveNet, an AI technology making machines sound more like humans. The system generates voices by sampling real human speech and directly modeling audio waveforms based on it, as well as its previously generated audio.[46][47][48][49]

DeepMind unveils an AI “working memory” able to learn how to solve tasks for itself, such as how best to get from A to B on the London tube network. The AI combines both data processing with self-learning code. The new algorithm is able to retain information in its memory and use its learnings to solve problems in some areas.[50][51][52]

2016

November 4

Partnership

DeepMind teams with Blizzard Entertainment to release an open test environment within the StarCraft II game for artificial intelligence researchers to use worldwide. DeepMind would use deep reinforcement learning to develop an AI agent that can play StarCraft II effectively.[53][54][55]

2016

November 22

Partnership

DeepMind announces a five-year agreement with a UK National Health Service trust that would give it access to patient data to develop and deploy its healthcare app, Streams. The agreement lasts until at least 2021.[56][57][58]

2016

December 5

Userbase

DeepMind announces open-sourcing DeepMind Lab, its 3D game-like platform for agent-based AI research, so that others can try and make advances in the field of AI. The DeepMind Lab project was used to create enviroments capable of testing AI systems’ ability to achieve goals in a wide range of environments. Tasks such as navigation in mazes, collecting fruit, traversing dangerous passages, laser tag and interaction with bots have been developed to refine the programs. The development of mazes and challenges were designed using video game Quake III Arena’s 17-year-old software, to teach its artificial intelligence programs how to operate in 3D spaces.[59][60][61][62]

2016

December

International expansion

DeepMind Applied is anounced as a sub-team to be forming in Mountain View, California. This team is expected to be more closely involved with Google, working with the various product teams to help implement AI-based solutions.[63]

2016

Financial

DeepMind records £40.3 million (US$ 52 million) in revenue in the year.[64]

2017

January

Collaboration

DeepMind's experts pledge to pass on their knowledge to students enrolled on machine learning master's programs at University College London.[65]

DeepMind announces development of a new way to protect confidential health data from itself, in an attempt to assure hospitals, and the public at large, that patient confidentiality isn’t compromised as DeepMind processes the sensitive medical health records entrusted to it.[66][67]

DeepMind develops algorithms that can anticipate energy demand and supply, with the potential to cut the United Kingdom energy consumption by up to 10%.[68][69][70][71]

2017

April 17

Userbase

DeepMind open sources TensorFlow library Sonnet, its object-oriented neural network library. Sonnet is a higher-level library that meshes well with DeepMind’s internal best-practices for research.[72][73]

2017

May

Controversy

Sky News publishes a leaked letter from the National Data Guardian, Dame Fiona Caldicott, revealing that in her "considered opinion" the data-sharing agreement between DeepMind and the Royal Free took place on an "inappropriate legal basis".[74]

2017

June

Partnership

DeepMind’s safety team partners with OpenAI in the development of an algorithm which can infer what humans want by being told which of two proposed behaviors is better. The learning algorithm uses small amounts of human feedback to solve modern reinforcement learning environments.[75]

DeepMind uses reinforcement learning to master parkour, using a virtual course designed by the researchers which features drops, hurdles, and ledges. All of the navigation is self-taught by the AI using a trial-and-error approach to working out how to move forward and progress across the course as fast as possible.[80][81]

DeepMind releases a paper describing new developments for "imagination-based planning" to AI and algorithms that simulate the human ability to construct plans. The AI can reason through decisions and make plans for the future, without being bound by human instructions.[82][83][84][85]

2017

October 4

Team

DeepMind launches DeepMind Ethics & Society (DMES), a new research group recruiting advisers from academia and charity sector with the purpose to ‘help technologists put ethics into practice’ and help coping with artificial intelligence to consider the “real-world impacts” of replicating human intelligence. The group consists of six independent research fellows, eight full-time researchers, and nine partnerships with other research institutions. It would explore topics such as algorithmic bias, accountability, and autonomous killing machines.[86][87][88]

DeepMind announces AlphaGo Zero, a software capable of mastering the Chinese game of Go without help from human players. The new version is an improvement on the original AlphaGo, which had to be trained over time using large quantities of human knowledge and supervision.[89][90][91][92][93]

DeepMind team introduces AlphaZero, a program using generalized AlphaGo Zero's approach, which achieved within 24 hours a superhuman level of play in chess, shogi, and Go, defeating world-champion programs, Stockfish, Elmo, and 3-day version of AlphaGo Zero in each case.[100]

2017

Financial

DeepMind records £54.4 million (US$ 71 million) in revenue in 2017, up 35% from £40.3 million (US$ 52 million) in 2016.[64]

2018

February

Partnership

DeepMind announces that it is teaming with the U.S. Department of Veterans Affairs in an attempt to use machine learning to predict the onset of acute kidney injury in patients, and also more broadly the general deterioration of patients during a hospital stay so that doctors and nurses can more quickly treat patients in need.[101]

DeepMind develops an artificial intelligence capable of an ability that most children only develop at around age 4, which is to infer what someone else is thinking. This new technology is thought to have useful application in the future, from warfare to elderly care.[102][103][104]

2018

March

International expansion

DeepMind announces a new research lab in Paris, led by Remi Munos.[105]

DeepMind develops a neural network that teaches itself to ‘imagine’ a scene from different viewpoints, based on just a single image. The new type of computer vision algorithm can generate 3D models of a scene from 2D snapshots, unraveling details from the static images and solving spatial relationships, including the camera’s position. Dubbed a Generative Query Network (GQN), the system gets rid of labels and focuses on what's known as unsupervised learning.[110][111][112][113]

2018

June 15

Controversy

The DeepMind Health Independent Reviewers’ 2018 report warns about the potential for DeepMind Health to be able to “exert excessive monopoly power” as a result of the data access and streaming infrastructure that’s bundled with provision of the Streams app, which would position DeepMind as the access-controlling intermediary between the structured health data and any other third parties.[114][115]

DeepMind partners with OpenAI in a new paper that proposes a new method to train reinforcement learning agents in ways that enables them to surpass human performance. The paper, titled Reward learning from human preferences and demonstrations in Atari, introduces a training model that combines human feedback and reward optimization to maximize the knowledge of RL agents.[118]

DeepMind presents a paper titled "Measuring abstract reasoning in neural networks", which details its attempt to measure various AIs’ abstract reasoning capabilities, much like IQ tests for humans.[120][121]

2018

July 18

Commitment

DeepMind, along with tech leaders, including Elon Musk, sign a pledge promising to not develop “lethal autonomous weapons.” They also call on governments to institute laws against such technology. The pledge is organized by the Future of Life Institute, an outreach group focused on tackling existential risks.[122][123][124]

DeepMind announces a partnership with Unity Technologies with the purpose to accelerate machine learning and artificial intelligence research. The new collaboration would focus on "virtual environments" that DeepMind can use to test and visualize experimental algorithms.[129][130][131][132]

DeepMind furthers cancer research and announces having been given access to mammograms from roughly 30,000 women that were taken at Jikei University Hospital in Tokyo, Japan between 2007 and 2018. The data would be used to refine DeepMind's AI breast cancer detection algorithms.[133][134]

2018

November 13

Team

Google announces DeepMind’s health care unit to be absorbed to the holding company to create an ‘AI assistant for nurses and doctors’.[135][136]

DeepMind develops an algorithm aimed at boosting wind energy efficiency. Google reports having increased energy production by 20% after installing its own AI software across its largest renewable energy facilities in the United States.[147][148]

DeepMind researchers develop an AI tasked with teaching itself to solve arithmetic, algebra and probability problems, among others. However, the neural network performs poorly when tested on a maths exam taken by 16-year-olds in the United Kingdom, getting just 14 out of 40 questions correct, or the equivalent of an E grade.[153][154]